Documents, including legal contracts, are becoming increasingly complex, varied and unstructured. It takes a skilled human to understand and analyze documents to break them into their constituent clauses and sections. Years of training and experience may be required to ensure that the content and structure are well understood before a new document can be analyzed and broken down effectively. Unfortunately, this is an individual, manual, tedious, time consuming and expensive process and does not use the collective experience of a large number of people. People who routinely deal with new documents could benefit significantly from an automated process for breaking a document down to a semantic structure that has meaning in the context of the document and the domain and business that the document refers to or affects.
Analyzing a document manually is a time consuming and error prone process. The accuracy of the results is also heavily dependent on the experience and training of the person performing the process. Additionally, the manual way of extraction does not leverage the collective intelligence of people who understand the structure and the business.
Further, it is not enough to break a document down into its constituent clauses and sections—these clauses and sections also need to be surfaced when required—for example, when taking an action on a contract like approving a contract, it is useful to see the contract broken down to its constituents when reading it before approval.
Existing solutions are not designed to handle arbitrary structures well within the context and the domain and the business process and do not benefit from a large corpus of pre-catalogued data. They do not surface this information in the context of the business process. Thus, it is with respect to these considerations and others that the present invention has been made.